📚 International A-Level Physics PH03 Unit 3 Formula Derivation Guide | 国际 A-Level 物理 PH03 单元三公式推导指南
In Edexcel International A-Level Physics Unit 3 (PH03), practical skills and data analysis are central. Mastering the derivations of uncertainty formulas, linearisation techniques, and graphical analysis is essential for high-scoring responses. This guide walks through key formula derivations with clear steps, helping you understand how experimental uncertainties combine and how to extract physical constants from linearised graphs.
在 Edexcel 国际 A-Level 物理单元三 (PH03) 中,实验技能与数据分析是核心。掌握不确定度公式的推导、线性化技巧以及图像分析方法,是获得高分的关键。本文带你逐步推导关键公式,帮助你理解实验不确定度如何合成,以及如何从线性化图像中提取物理常数。
1. Combining Uncertainties: Addition and Subtraction | 不确定度组合:加减法
When two measured quantities A and B are added or subtracted to give Q = A + B or Q = A − B, the absolute uncertainties ΔA and ΔB combine. If the errors are independent and random, the standard formula uses the root-sum-square (RSS) method: ΔQ = √[(ΔA)² + (ΔB)²]. This arises because the variance of a sum of independent variables equals the sum of their variances.
当两个测量量 A 和 B 相加或相减得到 Q = A + B 或 Q = A − B 时,绝对不确定度 ΔA 和 ΔB 会合成。若误差是独立且随机的,标准方法采用方和根 (RSS) 法:ΔQ = √[(ΔA)² + (ΔB)²]。这是因为独立变量之和的方差等于各自方差之和。
A simpler worst-case estimate often used in quick checks is to add the absolute uncertainties linearly: ΔQ ≈ ΔA + ΔB. However, for PH03 analysis involving multiple measurements, the quadrature sum is expected unless the question specifies a ‘worst-case’ approach.
在快速检验中常用的更简单的保守估计,是直接将绝对不确定度线性相加:ΔQ ≈ ΔA + ΔB。但在 PH03 涉及多次测量的分析中,除非题目明确要求”最坏情况”,否则应使用平方和开方。
2. Combining Uncertainties: Multiplication and Division | 不确定度组合:乘除法
For Q = A × B or Q = A / B, it is the relative (fractional) uncertainties that combine simply. The general error propagation formula for independent variables yields (ΔQ/Q)² = (ΔA/A)² + (ΔB/B)², so ΔQ = Q √[(ΔA/A)² + (ΔB/B)²]. In percentage terms, the percentage uncertainty in Q is the square root of the sum of squares of the percentage uncertainties in A and B.
对于 Q = A × B 或 Q = A / B,相对(分数)不确定度的合成更为简便。独立变量的通用误差传播公式给出 (ΔQ/Q)² = (ΔA/A)² + (ΔB/B)²,因此 ΔQ = Q √[(ΔA/A)² + (ΔB/B)²]。以百分比表示,即 Q 的百分比不确定度等于 A 和 B 的百分比不确定度平方和的平方根。
To see the origin, consider Q = A / B. The partial derivatives are ∂Q/∂A = 1/B and ∂Q/∂B = −A/B². Squaring and multiplying by the variances gives (ΔQ)² = (1/B²)(ΔA)² + (A²/B⁴)(ΔB)². Dividing by Q² = A²/B² returns the fractional uncertainty formula above.
溯源来看,对 Q = A / B 求偏导得 ∂Q/∂A = 1/B,∂Q/∂B = −A/B²,平方后乘以方差可得 (ΔQ)² = (1/B²)(ΔA)² + (A²/B⁴)(ΔB)²。两边除以 Q² = A²/B² 便得到上述相对不确定度公式。
3. Uncertainty in a Power Law Q = k Aⁿ | 幂函数 Q = k Aⁿ 的不确定度
When a quantity is raised to a power n, the relative uncertainty scales by the magnitude of that power. For Q = k Aⁿ where k is a constant and ΔA is the uncertainty in A, the propagation gives ΔQ/Q = |n| (ΔA/A). This follows from taking the logarithmic differential: d(ln Q) = n d(ln A), so dQ/Q = n dA/A.
当物理量被升幂 n 时,相对不确定度会被该幂的绝对值所放大。对于 Q = k Aⁿ(k 为常数,A 的不确定度为 ΔA),传播公式为 ΔQ/Q = |n| (ΔA/A)。这源自对数微分:d(ln Q) = n d(ln A),从而 dQ/Q = n dA/A。
In practice, if you measure a diameter d to find volume V = (4/3)π(d/2)³, the relative uncertainty in V is three times the relative uncertainty in diameter: ΔV/V = 3 (Δd/d). The factor arises because radius is proportional to diameter, and volume depends on radius cubed.
实际应用中,若测量直径 d 以求体积 V = (4/3)π(d/2)³,V 的相对不确定度便是直径相对不确定度的三倍:ΔV/V = 3 (Δd/d)。该因子之所以出现,是因为体积依赖于半径的三次方。
4. Linearisation of Non-Linear Relationships | 非线性关系的线性化
Many physical laws are not linear but can be transformed into a straight-line form. The pendulum equation T = 2π√(L/g) becomes T² = (4π²/g)L, giving a straight line through origin when plotting T² against L. For a power law y = k xⁿ, taking base-10 logarithms yields log₁₀ y = n log₁₀ x + log₁₀ k, which matches Y = m X + c with slope n and intercept log₁₀ k.
许多物理定律并非线性,但可通过变换转化为直线形式。单摆公式 T = 2π√(L/g) 化为 T² = (4π²/g)L,作 T²-L 图可得一条过原点的直线。对于幂函数 y = k xⁿ,取常用对数得 log₁₀ y = n log₁₀ x + log₁₀ k,即直线形式 Y = m X + c,其中斜率 m = n,截距 c = log₁₀ k。
Exponential relationships such as I = I₀ e⁻⁴λt are linearised by taking the natural logarithm: ln I = ln I₀ − λt. The gradient of the ln I vs t graph equals −λ. Linearisation not only simplifies the determination of constants but also makes uncertainty analysis more straightforward by allowing the use of linear regression and graphical max/min slope methods.
指数关系如 I = I₀ e⁻⁴λt 可通过取自然对数线性化:ln I = ln I₀ − λt。ln I-t 图的斜率即为 −λ。线性化不仅简化了常数的测定,
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